The predictive power of 18F-FDG PET/CT two-lesions radiomics and conventional models in classical Hodgkin’s Lymphoma: a comparative retrospectively-validated study

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Abstract In a previous preliminary study, radiomic features from the largest and the hottest lesion in baseline 18F-FDG PET/CT (bPET/CT) of classical Hodgkin’s Lymphoma (cHL) predicted early response-to-treatment and prognosis. Aim of this large retrospectively-validated study is to evaluate the predictive role of two-lesions radiomics in comparison with other clinical and conventional PET/CT models. cHL patients with bPET/CT between 2010 and 2020 were retrospectively included and randomized into training-validation sets. Target lesions were: Lesion_A, with largest axial diameter (Dmax); Lesion_B, with highest SUVmax. Total-metabolic-tumor-volume (TMTV) was calculated and 212 radiomic features were extracted. PET/CT features were harmonized using ComBat across two scanners. Outcomes were progression-free-survival (PFS) and Deauville Score at interim PET/CT (DS). For each outcome, three predictive models and their combinations were trained and validated: - radiomic model “R”; - conventional PET/CT model “P”; - clinical model “C”. 197 patients were included (training = 118; validation = 79): 38/197 (19%) patients had adverse events and 42/193 (22%) had DS ≥ 4. In the training phase, only one radiomic feature was selected for PFS prediction in model “R” (Lesion_B F_cm.corr, C-index 66.9%). Best “C” model combined stage and IPS (C-index 74.8%), while optimal “P” model combined TMTV and Dmax (C-index 63.3%). After internal validation, “C”, “C + R”, “R + P” and “C + R + P” significantly predicted PFS. The best validated model was “C + R” (C-index 66.3%). No model was validated for DS prediction. In this large retrospectively-validated study, a combination of baseline 18F-FDG PET/CT two-lesions radiomics and other conventional models showed an added prognostic power in patients with cHL. As single models, conventional clinical parameters maintain their prognostic power, while radiomics or conventional PET/CT alone seem to be sub-optimal to predict survival.

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